Robert Boldi1 Earle Williams2, and Anirban Guha3
1College of Sustainability Sciences and Humanities, Zayed University, Dubai, United Arab Emirates
2Parsons Laboratory, Massachusetts Institute of Technology, Cambridge Massachusetts, USA.
3Tripura University, Tripura, India.
Source: academia.edu
ABSTRACT:
A variety of putative influences upon Schumann resonance (SR) signals have been evaluated for the case of a 20 year record of measurements of two magnetic-field detectors and one electric-field detector located at West Greenwich Rhode Island, U.S.A. (71.6W, 41.6N).
The detector-specific SR signals considered are the values of the parameters of the first six modes of an eight-mode, three-parameter, Lorentzian-line-shape model.
The three parameters of the model are peak-center frequency, peak-quality factor, and peak intensity.
This model was used to fit the daily-average Fourier-transform intensity spectra spanning the frequency range 3 Hz - 56 Hz.
This results in 54 SR signals: 3 channels 6 modes / channel 3 parameters / mode.
We also computed an expected climatological-daily-average intensity spectra for each day and detector and fit these spectra to the above mentioned Lorentzian model.
A linear regression of the observed parameters to the expected parameters finds that on average the climatological-daily-average data account for 35% of the variance (R2 = 0.35) of the original SR series, with the best fits obtained for the Lorentzian-fit parameter peak-intensity where 70% of the variance of the original series was explained.
Averaging across channels and parameters, the second and third modes were best modeled by the climatological-average data, explaining 50% of the total variance; all above results are significant at the p 0:001 level.
We then subtracted the observed SR signals from the expected SR signals to generate residual SR signals.
The residual SR time series display a systematic variation following the 11-year sunspot cycle. A linear regression of a nominal sunspot cycle with the residual time series averaged across all modes and channels,
finds R2 values for peak-center frequency = 0.59, peak-quality factor = 0.31, and peak intensity = 0.0.
Averaging the residual time series across all modes and fit parameters, the sunspot cycle is found in each
channel; the R2 value for the E/W channel = 0.30, the R2 for the N/S channel = 0.37, and the R2 value for the Ez channel = 0.24 The sunspot-cycle pattern is strongest the mode 1 data (R2 = 0.48) and decreases with
increasing mode number; the R2 for mode 6 = 0.15; all significant at the p 0:001 level.
We then examined various putative influences upon these residual SR signals using a variety of techniques.
The results indicate that direct measures of solar activity (e.g. sunspot number and area) most strongly influence peak-center frequency and peak-quality factor (median R2 = 0.50) and less so the peak intensity
(median R2 = 0.02). Terrestrial temperature signals (e.g. Ocean temperature anomalies) influence peak-intensity (median R2 = 0.15) but not peak-center frequency nor peak-quality factor (median R2 = 0.01).
We also examined the spectral characteristics of the residual SR signals.
Both the peak-center frequency and peak-quality factor parameters, averaged over all of the modes and channels, display strong peaks at 11 years, 365 days, 180 days; in contrast, the peak-intensity parameter displays no similar features.
This indicates that the values of the peak intensity parameter are well predicted by the global total lightning and the uniform-cavity model, while the peak-center frequency and peak-quality factor parameters are not.
The values of these two parameters have a significant variation over the sunspot cycle unaccounted for by the
global total lightning and the uniform-cavity model.
Comments